No political censorhip? Try asking Chinese models about Taiwan.
Some censorhip and bias towards certain ideology is baked into those models.
While it is not a problem for programming tasks, I would never use it for certain other tasks.
No political censorhip? Try asking Chinese models about Taiwan.
Some censorhip and bias towards certain ideology is baked into those models.
While it is not a problem for programming tasks, I would never use it for certain other tasks.
> No political censorhip? Try asking Chinese models about Taiwan.
Self-hosting means being able to use abliterated models where the superficial instructions like not describing Taiwan as independent are burned off.
Censorship and bias are related but not synonymous. I agree that it's harder to remove political bias when the training data includes it. We know many of the frontier models are heavily trained on Reddit, for example, [which likely explains why we see such heavy left wing bias.](https://trakkr.ai/bias/findings)
More citations:
https://www.gsb.stanford.edu/faculty-research/working-papers... (article: https://news.stanford.edu/stories/2025/05/ai-models-llms-cha...)
https://www.tandfonline.com/doi/full/10.1080/29974100.2026.2...
https://ieeexplore.ieee.org/document/10817610
https://www.washingtonpost.com/technology/interactive/2026/0...
https://link.springer.com/article/10.1007/s11127-023-01097-2
All good points, but I am not sure who I trust less. Chinese companies or random people on Hugging Face. :) It is still a black box. And I have a feeling I could not abliterate those models on my own hardware.
I am not saying I would not use any of them at all, but I would avoid doing certain tasks with them. And with the testing I have done with abliterated models in the past, it is not 100% successful and it can still hit the same walls as original model.
So... the Super Intelligence is Democrat?